Multi-signal Source Identification of ELM Hammerstein Model with Colored Noise

被引：0
|
作者：
Han, Zhenzhen [1 ,2 ]
Cheng, Bin [1 ,2 ]
Wang, Yunli [1 ,2 ]
Shao, Yunxia [1 ,2 ]
机构：
[1] Hebei Acad Sci, Inst Appl Math, Shijiazhuang 050081, Hebei, Peoples R China
[2] Hebei Authenticat Technol Engn Res Ctr, Shijiazhuang, Hebei, Peoples R China
来源：
2018 IEEE 3RD INTERNATIONAL CONFERENCE ON CLOUD COMPUTING AND BIG DATA ANALYSIS (ICCCBDA) | 2018年
关键词：
hammerstein model; extreme learning machine; Multi-signal source; recursive extended least squares algorithm; identification;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Hammerstein model is used in practical industrial process widely. A novel ELM-Hammerstein model with colored noise is proposed, where the extreme learning machine (ELM) is used to describe static nonlinear part and the dynamic linear part is described by CARAR model. The purpose is to identify the parameters of ELM-Hammerstein model. But, intermediate signal can not measure directly in the process of identification. So special signal is employed to separate the static nonlinear part and the dynamic linear part of the Hammerstein model. Further, recursive extended least squares (RELS) algorithm is applied to compute the unknown parameters of linear part. As a result, the proposed method can describe the nonlinear system with colored noised with high accuracy. Simulation example demonstrates its effectiveness.
引用
收藏
页码：457 / 461
页数：5
相关论文
共 50 条
  • [21] System identification: a multi-signal approach for probing neural cardiovascular regulation
    Xiao, XS
    Mullen, TJ
    Mukkamala, R
    PHYSIOLOGICAL MEASUREMENT, 2005, 26 (03) : R41 - R71
  • [22] Hierarchical stochastic gradient identification for non-uniformly sampling hammerstein systems with colored noise
    Liu Ranran
    Zheng Enxing
    Chang Shan
    Bei Shaoyi
    Zhang Lanchun
    COMPUTER SYSTEMS SCIENCE AND ENGINEERING, 2016, 31 (06): : 425 - 430
  • [23] Identification of a Class of Multi-signal Based Neuro-fuzzy Wiener Systems
    Li, Yangyang
    Jia, Li
    Li, Feng
    Xiong, Qi
    Gao, Sheng
    PROCEEDINGS OF 2018 IEEE 7TH DATA DRIVEN CONTROL AND LEARNING SYSTEMS CONFERENCE (DDCLS), 2018, : 85 - 90
  • [24] NONLINEAR IDENTIFICATION IN PRESENCE OF CORRELATED NOISE USING A HAMMERSTEIN MODEL
    HAIST, ND
    CHANG, FHI
    LUUS, R
    IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 1973, AC18 (05) : 552 - 555
  • [25] Blind Source Separation for OFDM with Filtering Colored Noise and Jamming Signal
    Sriyananda, M. G. S.
    Joutsensalo, Jyrki
    Hamalainen, Timo
    JOURNAL OF COMMUNICATIONS AND NETWORKS, 2012, 14 (04) : 410 - 417
  • [26] Identification methodology for MIMO Hammerstein nonlinear model with process noise
    Li, Feng
    Sun, Xueqi
    Wang, Tianhu
    Liu, Ranran
    TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL, 2024,
  • [27] Wide area PSS coordinated design based on multi-signal online identification
    Yuan, Ye
    Sun, Yuanzhang
    Cheng, Lin
    Dianli Xitong Zidonghua/Automation of Electric Power Systems, 2010, 34 (08): : 14 - 19
  • [28] Information Fusion Identification Method for ARMA Signal with Colored Measurement Noise
    Zhang, Mingbo
    PROCEEDINGS OF 2013 2ND INTERNATIONAL CONFERENCE ON MEASUREMENT, INFORMATION AND CONTROL (ICMIC 2013), VOLS 1 & 2, 2013, : 384 - 388
  • [29] Extracting weak multi-frequency signal in heavy colored noise
    Yang, Chen
    Yang, Jianhua
    Zhang, Shuai
    Liu, Houguang
    JOURNAL OF THE BRAZILIAN SOCIETY OF MECHANICAL SCIENCES AND ENGINEERING, 2020, 42 (11)
  • [30] Extracting weak multi-frequency signal in heavy colored noise
    Chen Yang
    Jianhua Yang
    Shuai Zhang
    Houguang Liu
    Journal of the Brazilian Society of Mechanical Sciences and Engineering, 2020, 42
12345